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Gemini 4 Argon teaches robot to play cornhole, slashing engineering time

Google's Gemini 4 Argon model has enabled a humanoid robot, named Apollo, to learn how to play cornhole by observing a single human video. The AI developed its own physics simulator to train the throwing motions and then refined these skills on the actual robot, achieving seven consecutive successful shots. This advancement significantly reduces the time and engineering effort required for robotics training, compressing weeks of work into mere hours. AI

IMPACT Accelerates robotics training by enabling rapid skill acquisition from limited data, potentially speeding up deployment of humanoid robots.

RANK_REASON The item describes a research milestone where an AI model enabled a robot to learn a new skill with reduced training time. [lever_c_demoted from research: ic=1 ai=1.0]

Read on r/singularity →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Gemini 4 Argon teaches robot to play cornhole, slashing engineering time

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The item describes a research milestone where an AI model enabled a robot to learn a new skill with reduced training time. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. r/singularity TIER_2 English(EN) · /u/141_1337 ·

    Google's Gemini 4 Argon taught a humanoid robot to play cornhole from a single human video. It built its own physics simulator, trained the throws, and refined them on the real robot. Apollo then landed 7 shots in a row. Google says this cuts weeks of robotics engineering down to hours.

    <table> <tr><td> <a href="https://www.reddit.com/r/singularity/comments/1x58mbn/googles_gemini_4_argon_taught_a_humanoid_robot_to/"> <img alt="Google's Gemini 4 Argon taught a humanoid robot to play cornhole from a single human video. It built its own physics simulator, trained t…